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Antecontractul de vânzare-cumpărare a unui imobil
Antecontractul de vânzare-cumpărare a unui imobil, numit și promisiune de vânzare-cumpărare sau precontract, este un act încheiat la notariat în formă autentică prin care proprietarul unui imobil se obligă faţă de o altă persoană să i-l vândă acesteia în viitor. Antecontractul se poate încheia la orice notar public din România, indiferent de localizarea imobilului sau de domiciliul părților.
Antecontractul de vânzare-cumpărare îmbracă în practică forma a juridică a unei:
(1) promisiuni unilaterale, cât şi a unei
(2) promisiuni bilaterale de vânzare-cumpărare.
(1) Promisiunea unilaterală de vânzare este un contract unilateral prin care promitentul proprietar se obligă faţă de o altă persoană să îi vândă acesteia în viitor un anumit bun al său. Această persoană îşi rezervă dreptul să-şi exprime ulterior, în cadrul unui termen, consimţământul de a cumpăra bunul în cauză. Contractul poate fi transformat într-unul sinalagmatic prin obligarea beneficiarului promisiunii la plata unei sume de bani în contul dreptului său de opţiune.
(2) Promisiunea bilaterală de vânzare-cumpărare reprezintă situaţia în care ambele părţi se obligă să încheie în viitor, în condiţiile stabilite de antecontract, contractul propriu-zis de vânzare-cumpărare. Principala deosebire faţă de promisiunea unilaterală este că în acest caz ambele părţi pot cere încheierea contractului. Precontractului de vânzare-cumpărare îi sunt aplicabile dispoziţiile art. 969 şi urm. C. civ. (regulile aplicabile convenţiilor).
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I haven’t figured it out. Out of frustration, I also downloaded the Google keyboard. I get the impression that Apple does not want to recognize the issue much less try to resolve it. The response I got from them was that they couldn’t reproduce the problem. I find that hard to believe unless they only tried to swipe „you” as the first word and stopped there.
I am not the only person with this issue. If you swipe „you” as the first word of a text message it works just fine but any subsequent „you” turns into „your”. This was never an issue before. Maybe it is a predictive issue and I should turn that feature off?
„In any app that allows text editing, open the onscreen keyboard by tapping a text field. Tap individual keys to type, or use QuickPath to type a word by sliding from one letter to the next without lifting your finger (not available for all languages). To end a word, lift your finger. You can use either method as you type, and even switch in the middle of a sentence. (If you tap after sliding to type a word, it deletes the whole word.)
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Not necessarily, Google is still more likely than other apps to find a way to send your keyboard input to its mothership through Play Services or one of the many other apps they control and people might need (like Google Maps). In theory taking away network permission is working great, but mutual data sharing consent between apps can break this if you’re not careful.
N3rdTek In fact a very common procedure is to install Google keyboard, go into the settings so you can enable faster voice typing, once that finishes you disable network, and now you have voice typing without a keyboard phoning home if you happen to be worried about that.
To my knowledge voice typing without internet access is subpar compared to voice typing with internet access. But nowadays I recommend FUTO Voice Input anyway, because it’s great, open source and works offline. Plus it can be used in combination with a lot of Open Source Keyboards so you’re not limited to one keyboard app that might not fit your needs.
I second this. If you turn off Networking then Swiftkey is reasonably private. There’s a possibility it might communicate with other Microsoft apps, but I haven’t seen any evidence of that specifically happening. Swiftkey also has an „incognito” mode that you can leave permanently enabled, but the downside is the predictive suggestions won’t learn from your writing style (which Swiftkey is actually really good at). I think clipboard might also not work well in incognito mode? But I haven’t fully tested that.
Tfur Security? Well, without network permissions is like, they can’t take away the data even if they want, right? I’ve been using Swiftkey since they’re out, way back before Microsoft. Love their prediction, customization and options. But well, if someone come to me and say that it’s somehow not secure and they’re getting my data anyway I’ll have to find a replacement. Couldn’t find any yet.
I have been using TouchPal for years and moved it from phone to phone. On my new GP7Pro however, it just will not install on Graphene. I’d like to know if its the hardware, Android version, or Graphene – Anyone know? It appears in the store, downloads and (and the version I use) attempts to install, but just won’t. I actually used an older version… I found that after a certain version, the bloat (emojis, games, ads, links etc) got ridiculous, so I found a site that hosted all versions available for download, so I tried a bunch till I found the 1 that had the best features with the lest bloat.
So, I’ve tried Floris, and a couple of others. Microsoft is the best so far but still quite lacking by comparison. The swipe left on delete key doesn’t seem to work on any and the movement through text is not the greatest.
DeletedUser28 Oh yes! At first I thought it was bit of balloney as when I installed the OpenBoard APK there was no gesture typing available, but at that link I saw that they provided the gesture typing libraries from the Google board separately, as there was no open source one (yet). And I also found the setting where it asked for a gesture library to add in OpenBoard. So I downloaded the arm64 one, prompted OpenBoard to the library file and viol! In a way much better than Gboard, as somehow it won’t catch on to the language libraries.
In fact a very common procedure is to install Google keyboard, go into the settings so you can enable faster voice typing, once that finishes you disable network, and now you have voice typing without a keyboard phoning home if you happen to be worried about that.
N1b Old post, but I thought I’d add my two cents…………..I recently switched over to FUTO voice and keyboard after the GBoard and Google voice-to-text solution inexplicably quit working. I am very happy with FUTO so far and have had no issues with the keyboard which is in Alpha. I would recommend at least giving it a try. I am excited about it so far and am happy to have deleted those disgusting Google apps from my device.
The main reason I use Swiftkey (even before the Microsoft takeover) is the row of numbers above the letters and the row of arrows that allow me to move the cursor around without having to delete nearly everything I typed in before. FUTO voice sounds exciting. I have to admit that I have been very reluctant to use voice commands, although it can be a time saver.
Just to clarify, things have moved on a bit since this solution was posted. You can still do the down swipe above the keyboard, which is standard in the OS, but you can also just use the keyboard button on the right of the bar (iPhone), or use the standard hide-keyboard button on the iPad (bottom-right).
The new swype-style keyboard on my 4.2.1 updated Galaxy Nexus is great. However, when I attempt to express myself more colorfully, the swiping action does not yield the word I would like to write. The word is already in the device dictionary though, so it does not let me add it to the dictionary to be recognized, as I have done with other words. Does anyone know how to fix this?
I can now swype swear words, although often times it is not the automatically recognized word, and I have to manually select it from the list of other possibilities that comes up. As for the voice-to-text options, I would suggest trying the same thing (i.e. finding it under Settings and deselecting Block offensive words or some similar option). Hope this helps!
Is there any way to use swipe (swype) typing on the on-screen keyboard? By swipe typing I mean keeping a finger (or pen) touching the keyboard and moving from key to key without lifting. On Android this allows writing words in one gesture.
With your query, yes, the on-screen keyboard in Windows 11 supports swipe typing, which is also known as „shape writing.” To enable swipe typing on your Surface Pro 7+ running Windows 11, follow these steps:
There is no „Shape writing” option in the keyboard settings menu on any of the keyboard types, nor does the Setting Search find anything. The only reference to „shape writing” I can find is in relation to eye tracking which is not what I’m asking about.
The question I’m asking is about swipe typing, sometimes spelled „swype”. Swipe typing is a method of keyboard input where you touch a key and without lifting your finger slide to other keys to spell out a word, all without lifting your finger until the end. This is very common on phones. https://drive.google.com/file/d/11MtnAS49zYqvP0ijSk15VaKwi4M8o6tH/view
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There are several studies conducting simulations of energy. Studies Kartikasari et al. and Shukla et al. share similar objectives, which are to evaluate the feasibility of solar photovoltaic power generation systems at their respective locations using simulation. However, a study by Kartikasari et al. was conducted in Surabaya, Indonesia, focusing on a 3 kWp rooftop photovoltaic system [24], while a study by Shukla et al. was conducted at MANIT, Bhopal, India, focusing on a 110 kWp rooftop photovoltaic system [25]. Both studies utilized SolarGIS PV Planner for simulation, although Study Kartikasari et al. also used RETScreen.
In addition, these studies discuss the importance of performance and economic analysis in the implementation of photovoltaic systems to support the transition to renewable energy. Research in Islamabad, Pakistan, using PVSyst to design PV systems in luxury villas and high-rise buildings, revealed that payback analysis and performance ratios are critical to assessing financial viability, both through direct purchase and bank financing [31]. In India, research showed that with government support, residential rooftop PV systems become more economically viable, and simulations using PVSyst compared different PV module technologies based on energy performance and long-term economic analysis [32]. Research in Bangladesh emphasized the efficiency and carbon emission reduction potential of grid-connected PV systems, where the systems have the potential for cost savings and generate revenue from selling electricity to the grid [33]. The findings suggest that a comprehensive technical and economic feasibility analysis before PV installation is essential to ensure sustainable energy benefits in various locations. Based on this research, we propose research related to the feasibility study of the photovoltaic system at the New Media Tower at Universitas Multimedia Nusantara using PVSyst. This analysis will include technical and economic evaluations.
This section describes the methodology used for the technical and economic analysis of the solar photovoltaic (PV) system on Building C at Universitas Multimedia Nusantara (UMN). The analysis process was carried out in two major phases: technical and economic evaluation to assess project feasibility. This analysis is conducted by using PVSyst software.
Initially, data collection involved a site survey of Building C and its surroundings. Data included the location as simulation objects, solar irradiance, and shading analysis. The survey also covered information on existing infrastructure that may impact photovoltaic system installation. This information was critical for system orientation and shading simulations. For solar irradiance data, historical meteorological data for the region was obtained through the Meteonorm database, which provides location-specific irradiance values necessary for accurate simulations. The survey also took into account local weather conditions, which affect PV system performance.
Throughout the New Media Tower of Universitas Multimedia Nusantara, several locations with potential for photovoltaic installation were identified. The following will discuss two selected locations in more detail, considering the advantages and disadvantages of each location. The data presented will serve as the basis for design and near shading using PvSyst.
The rooftop of Building C in Fig 1 is one of the locations worth exploring because it is almost entirely free from shading effects from surrounding buildings, especially from Building C itself. The rooftop area is also relatively large, approximately 1,000 m2, thus having the highest potential to produce electricity in sufficient quantities to meet the target.
The outdoor motorcycle parking area is shown in Fig 2 located next to Buildings C and D. Because it is almost at the same level as the ground floor of the building, installing and maintaining PV systems is easier and more affordable than on the roof. However, the motorcycle parking area has two main obstacles: the presence of many trees and buildings C and D nearby, and the limited area of the motorcycle parking space. This limited area, approximately only 400 m2, reduces production output, and the presence of obstacles such as trees and buildings that create shading reduces the potential for electricity production here. Nevertheless, this location still appears feasible for analysis because if it can achieve production targets, installing and maintaining solar panels here will be much cheaper.
For analysis and target determination purposes, this data needs to be converted into annual data. Assuming that the electricity consumption in these three months represents a typical three-month period for electricity consumption throughout the year, and all buildings in Universitas Multimedia Nusantara (A, B, C, and D) consume electricity in equal amounts, the target value can be calculated as follows in Table 2. The target electricity generation value is 209,640 kWh per year or 209.64 MWh per year.
Once the site-specific data was gathered, system design and simulations were carried out using PVSyst software, a widely recognized tool for PV system design and energy yield prediction. The following steps were taken:
By incorporating the data obtained through site surveys, simulations were conducted using PVSyst software. Here is a detailed breakdown of all the simulation results. Below is a description of the types of equipment used in the simulation using PVSyst software.
Array sizing is the process of determining the number of solar panels based on the selected panel model, inverter, and either land area or system power plan to meet the specified target. This process can be done manually by adjusting the numbers in the Number of modules and strings section, or automatically by clicking the Resize button in the Pre-Sizing Help section. For this system, the following array sizing limits are used:
The system design process continues with the creation of a single-line diagram (SLD). SLD is a simple technical drawing representing the PV system design. In PVSyst, SLDs are automatically generated and accessible through the Single-line diagram button in the system definition menu.
To determine the amount of shading and when shading occurs for each panel installation, a near-shading scheme is created for both variants. Fig 3 below shows the 3D results used as input for the roof near shading simulation. Meanwhile, Fig 4 below shows the 3D results used as input for the outdoor motorcycle parking near-shading simulation. It can be observed that the number of objects in this near shading scheme is much higher because the placement of solar panels low to the ground and close to the surface increases the potential for near shading.
After designing the system following these steps, performance simulation and system production results can be initiated. The simulation results depend on the information from each previous step of system orientation, design, and near-shading schemes. The estimated system production is 2MWh/year for the rooftop and 64.5 MWh/year for parking area.
Among the two variants of solar photovoltaic system (PV) installation cases discussed, only the rooftop variant can approach the production target of 209.64 MWh/year. The simulation results indicate that the designed rooftop PV system can generate 202 MWh/year, which is very close to the target. On the other hand, the designed PV system in the parking area can only generate 64.5 MWh/year, significantly smaller than the target and the simulation results of the rooftop PV system.
Furthermore, looking at production performance, the parking system only produces 3.38 kWh/kWp/day, which means the production efficiency of the parking PV system is reduced by about 15% compared to the rooftop PV system, which produces 3.98 kWh/kWp/day. In short, the location of the PV system in the parking area is quite poor, especially due to the presence of many objects such as buildings and trees that contribute to shading around this parking area. Therefore, among the two locations, the rooftop of Building C itself stands out as the suitable site for PV system installation. https://drive.google.com/file/d/1eHtCINZNEl5M4sLtEP8pec_kxAqrJc8u/view
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